带你从零实现一个高性能的深度学习推理库，支持大模型 llama2 、Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library step by step

🧠 BPCAPooling, a custom pooling method that performs dimensionality reduction without loss of spatial information.

Ensemble Network Including Transformer Models for NLP Patient Text and ED Visit Prediction

Using convolutional neural networks to build and train a bird species classifier on bird pics data with corresponding species labels, also build GUI for the same.

This repository contains code that implemented Mask Detection using MobileNet as the base model and Neural Network as the head model. Code draws a rectangular box over the person's face in red if no mask, green if the mask is on, with 99% accuracy in real-time using a live webcam. Refer to README for demo

I used the MNIST dataset for the implementation of a handwritten digit recognition app. To implement this, will be using a special type of deep neural network called Convolutional Neural Networks. In the end, I also build a Graphical user interface(GUI) where you can directly draw the digit and recognize it straight away.

A Deep Learning framework for CNNs and LSTMs from scratch, using NumPy.

JavaFx Application for Convolutional Network to perfom Image Classification using Softmax Output Layer, Back Propagation, Gradient Descent, Partial Derivatives, Matrix Flattening, Matrix Unfolding, Concurrent Task, Performance Histogram, Confusion Matrix

Compute Sentence Embeddings Fast!

Written by Sem Kirkels, Nathan Bruggeman and Axel Vanherle. Grayscales an image, applies convolution, maximum pooling and minimum pooling.

implementation of neural network from scratch only using numpy (Conv, Fc, Maxpool, optimizers and activation functions)

This repository consists of models of CNN for classifying different types of charts. Moreover, it also includes script of fine-tuned VGG16 for this task. On top of that CradCAM implementation of fine-tuned VGG16.

Coronavirus tweets NLP - Text Classification mini-project work for Data Science course, FCSE, Skopje

Hi! Thanks for checking out my tutorial where I walk you through the process of coding a convolutional neural network in java from scratch. After building a network for a university assignment, I decided to create a tutorial to (hopefully) help others do the same and improve my own understanding of neural networks.

Making a footwear classification model using CNN.

This model helps us classify 10 different real-life objects by undergoing training under tensorflow's CIFAR dataset which contains 60,000 32x32 color images with 6000 images of each class. I have made use of a stack of Conv2D and MaxPooling2D layers followed by a few densely connected layers.

Sentiment Analysis Using Tensorflow

In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset.